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Spectral features of EEG in depression

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Published/Copyright: April 26, 2010
Biomedical Engineering / Biomedizinische Technik
From the journal Volume 55 Issue 3

Abstract

The aim of this study was to find distinctions of the EEG signal in female depression. Experiments were carried out on two groups of 18 female volunteers each: a group of patients with depressive disorder who were not on medication and a group of control subjects. Patients who had Hamilton depression rating scores higher than 14 were selected. Resting EEG was recorded for the duration of 30 min. Spectral asymmetry (SA) of the EEG spectrum was estimated as relative difference in the selected higher and lower EEG frequency band power. Calculated SA values were positive for depressive and negative for healthy subjects (except for 2–3 subjects). The values behaved similarly in all EEG channels and brain hemispheres. Differences in SA between depressive and control groups were significant in all EEG channels. Dependence of SA on EGG signal length appeared not to be identical for depressive and healthy subjects. Our results suggest that SA based on balance between the powers of the higher and the lower EEG frequency bands seems to enable characterization of the EEG in depression.

Keywords: depressive disorder; EEG analysis; EEG frequency; spectral asymmetry
Corresponding author: Hiie Hinrikus, Department of Biomedical Engineering, Technomedicum of Tallinn University of Technology, Ehitajate Rd 5, 19086, Tallinn, Estonia
Received: 2009-2-22
Accepted: 2009-12-2
Published Online: 2010-04-26
Published Online: 2010-04-26
Published in Print: 2010-06-01

©2010 by Walter de Gruyter Berlin New York

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https://doi.org/10.1515/bmt.2010.011
Keywords for this article
depressive disorder; EEG analysis; EEG frequency; spectral asymmetry

Articles in the same Issue

  1. Guest editorial
  2. NeuroMath: advanced methods for the estimation of human brain activity and connectivity
  3. Research articles
  4. The significance of relative conductivity on thin layers in EEG sensitivity distributions
  5. Comparison between realistic and spherical approaches in EEG forward modelling
  6. On the analysis of BIS stage epochs via fuzzy clustering
  7. Spectral features of EEG in depression
  8. On the role of cost-sensitive learning in multi-class brain-computer interfaces
  9. Spatial filters to detect steady-state visual evoked potentials elicited by high frequency stimulation: BCI application
  10. Control and data acquisition software for high-density CMOS-based microprobe arrays implementing electronic depth control
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